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This paper provides a pair similarity optimization viewpoint on deep feature learning, aiming to maximize the within-class similarity $s_p$ and minimize the between-class similarity $s_n$.
Learning a similarity metric discriminatively, with application to face verification
S. Chopra, R. Hadsell, and Y. LeCun · 2005
Earlier work this paper cites.
Dimensionality reduction by learning an invariant mapping
R. Hadsell, S. Chopra, and Y. LeCun · 2006
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Labeled faces in the wild: A database for studying face recognition in unconstrained environments
G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller · 2007
Earlier work this paper cites.
The Caltech-UCSD Birds-200-2011 Dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
Earlier work this paper cites.
Face recognition in unconstrained videos with matched background similarity
L. Wolf, T. Hassner, and I. Maoz · 2011
Earlier work this paper cites.
3d object representations for fine-grained categorization
J. Krause, M. Stark, J. Deng, and L. Fei-Fei · 2013
Earlier work this paper cites.
Deep learning face representation from predicting 10,000 classes
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Earlier work this paper cites.
Deep metric learning using triplet network
E. Hoffer and N. Ailon · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
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Earlier work this paper cites.
Facenet: A unified embedding for face recognition and clustering
F. Schroff, D. Kalenichenko, and J. Philbin · 2015
Earlier work this paper cites.
Scalable person re-identification: A benchmark
L. Zheng, L. Shen, L. Tian, S. Wang, J. Wang, and Q. Tian · 2015
Earlier work this paper cites.
Ms-celeb-1m: A dataset and benchmark for large-scale face recognition
Y. Guo, L. Zhang, Y. Hu, X. He, and J. Gao · 2016
Earlier work this paper cites.
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K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
The megaface benchmark: 1 million faces for recognition at scale
I. Kemelmacher-Shlizerman, S. M. Seitz, D. Miller, and E. Brossard · 2016
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Large-margin softmax loss for convolutional neural networks
W. Liu, Y. Wen, Z. Yu, and M. Yang · 2016
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Deep metric learning via lifted structured feature embedding
H. Oh Song, Y. Xiang, S. Jegelka, and S. Savarese · 2016
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Frontal to profile face verification in the wild
S. Sengupta, J.-C. Chen, C. Castillo, V. M. Patel, R. Chellappa, and D. W. Jacobs · 2016
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Improved deep metric learning with multi-class n-pair loss objective
K. Sohn · 2016
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Learning deep embeddings with histogram loss
E. Ustinova and V. S. Lempitsky · 2016
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A discriminative feature learning approach for deep face recognition
Y. Wen, K. Zhang, Z. Li, and Y. Qiao · 2016
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Attention-based ensemble for deep metric learning
W. Kim, B. Goyal, K. Chawla, J. Lee, and K. Kwon · 2018
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Iarpa janus benchmark-c: Face dataset and protocol
B. Maze, J. Adams, J. A. Duncan, N. Kalka, T. Miller, C. Otto, A. K. Jain, W. T. Niggel, J. Anderson, J. Cheney, et al · 2018
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Deep metric learning with bier: Boosting independent embeddings robustly
M. Opitz, G. Waltner, H. Possegger, and H. Bischof · 2018
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Beyond part models: Person retrieval with refined part pooling (and a strong convolutional baseline)
Y. Sun, L. Zheng, Y. Yang, Q. Tian, and S. Wang · 2018
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Additive margin softmax for face verification
F. Wang, J. Cheng, W. Liu, and H. Liu · 2018
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Learning discriminative features with multiple granularities for person re-identification
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In defense of the triplet loss for person re-identification
A. Hermans, L. Beyer, and B. Leibe · 2017
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Sphereface: Deep hypersphere embedding for face recognition
W. Liu, Y. Wen, Z. Yu, M. Li, B. Raj, and L. Song · 2017
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Deep metric learning via facility location
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L2-constrained softmax loss for discriminative face verification
R. Ranjan, C. D. Castillo, and R. Chellappa · 2017
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Normface: L2 hypersphere embedding for face verification
F. Wang, X. Xiang, J. Cheng, and A. L. Yuille · 2017
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Deep metric learning with angular loss
J. J. Wang, F. Zhou, S. Wen, X. Liu, and Y. Lin · 2017
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G. Wang, Y. Yuan, X. Chen, J. Li, and X. Zhou · 2018
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Cosface: Large margin cosine loss for deep face recognition
H. Wang, Y. Wang, Z. Zhou, X. Ji, D. Gong, J. Zhou, Z. Li, and W. Liu · 2018
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Person transfer gan to bridge domain gap for person re-identification
L. Wei, S. Zhang, W. Gao, and Q. Tian · 2018
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X. Zhang, F. X. Yu, S. Karaman, W. Zhang, and S.-F. Chang · 2018
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Arcface: Additive angular margin loss for deep face recognition
J. Deng, J. Guo, N. Xue, and S. Zafeiriou · 2019
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Softmax dissection: Towards understanding intra- and inter-clas objective for embedding learning
L. He, Z. Wang, Y. Li, and S. Wang · 2019
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Multi-similarity loss with general pair weighting for deep metric learning
X. Wang, X. Han, W. Huang, D. Dong, and M. R. Scott · 2019
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Adacos: Adaptively scaling cosine logits for effectively learning deep face representations
X. Zhang, R. Zhao, Y. Qiao, X. Wang, and H. Li · 2019
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Joint discriminative and generative learning for person re-identification
Z. Zheng, X. Yang, Z. Yu, L. Zheng, Y. Yang, and J. Kautz · 2019
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